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  • HeadStart heads up briefing 6: Targeted interventions in HeadStart: how do HeadStart partnerships support the mental health of young people, and do they reach those in need?

    In this briefing, we aim to illustrate the range of targeted interventions offered by six local authority led partnerships through the HeadStart programme. We also investigate whether these interventions reached young people with higher needs in terms of their mental health and wellbeing (2022).

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  • HeadStart heads up briefing 5: Gender differences, improving support, and talking about mental health: learning from the 2020 HeadStart conference

    This briefing draws on table discussions at the HeadStart Learning 2020 conference, which took place in February 2020. The event was a collaboration between the HeadStart Learning Team and The National Lottery Community Fund, with substantial input from young people involved in HeadStart from across the six partnerships (2020).

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  • Measuring pupil mental health and wellbeing: examples of best practice from schools and colleges working with the Mercers’ Company

    This briefing draws on learning emerging from research led by the Evidence Based Practice Unit in collaboration with the Child Outcomes Research Consortium, The University of Manchester and Common Room. The Mercers’ Company funded the research. The Mercers’ Company is the Premier Livery Company of the City of London. Authors: Deighton, J., Stapley, E., Lereya, T., Burrell, K., Atkins, L. (2019).

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  • Using flawed, uncertain, proximate and sparse (FUPS) data in the context of complexity: learning from the case of child mental health

    This paper presents an example of the use of a FUPS dataset in the complex system of child mental healthcare. The paper explores the use of this FUPS dataset to support meaningful dialogue between key stakeholders, including service providers, funders and users, in relation to outcomes of services. The term ‘FUPS’ is proposed to describe these flawed, uncertain, proximate and sparse datasets. Authors: Wolpert, M., Rutter, H. (2018).

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  • Prevalence of mental health problems in schools: poverty and other risk factors amongst 28,000 adolescents in England

    This study analyses a large-scale community-based dataset of 28 160 adolescents to explore school-based prevalence of mental health problems and characteristics that predict increased odds of experiencing them. Authors: Deighton, J., Lereya, T.L., Casey, P., Patalay, P., Humphrey, N., & Wolpert, M. (2019).

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  • An overview of developmental behavioral genetics

    In this chapter, we present an overview of the field of developmental behavioural genetics, which serves as important context for understanding the field of behavioral epigenetics. Authors: Austerberry, C., Fearon, P. (2020).

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  • The therapeutic process in psychodynamic therapy with children with different capacities for mentalizing

    The aim of this study was to explore the therapeutic process in psychodynamic therapy with school-age children with different kinds of difficulties and mentalizing profiles. Authors: Ramires, V., Carvalho, C., Goodman, G., Midgley, N. & Polli. R. (2020).

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  • How does the association between special education need and absence vary overtime and across special education need types?

    We investigated special education needs (SEN) as a risk factor for absenteeism. For 418,455 mainstream secondary school students from 151 local authorities in England, multilevel linear regression models were run to investigate the association between SEN, SEN types and absenteeism during their secondary school period from year 7 to year 11. Authors: Lereya, T., Cattan, S, Yoon, Y., Gilbert, R. & Deighton, J. (2022).

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